Past members

Mikkel Schmidt

Read more →

Marc Diesenroth

Read more →

Katherine Heller

Read more →

Jeroen Janssens

Read more →

Jean Pascal Pfister

Read more →

Henrik Ohlsson

Read more →

Frederik Eaton

Read more →

Finale Doshi

Read more →

Ali Bahramisharif

Read more →

Alex Ksikes

Read more →

Daniel M. Roy

Daniel received a Ph.D. in Computer Science at MIT under Leslie Kaelbling, following an MEng and BS in Electrical Engineering. He joined the group in March 2011 as a Newton Fellow of the Royal Society, and then as a research fellow of Emmanuel College. His work addresses theoretical questions at the foundation of the emerging field of probabilistic programming in AI and machine learning, and he has interests in the complexity of probabilistic inference; representation theorems connecting complexity and probabilistic structures; and the use of recursion to define nonparametric distributions on data structures.

Read more →

Neil Houlsby

Neil is a Google European Doctoral Fellow who started his PhD in Statistical Machine Learning in 2010, co-supervised by Zoubin Ghahramani and Mate Lengyel. In July 2014 he will start work at Google Research, Zurich. Current research interests include probabilistic models for matrices, active learning, variational inference and applications in cognitive science and psychometrics.

Read more →